Ben Fitzpatrick

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Contact: Phone: 310.338.7892 Email: Ben.Fitzpatrick@lmu.edu Office: University Hall 2753 Dr. Ben G. Fitzpatrick is the Clarence J. Wallen, S. J. Professor of Mathematics at Loyola Marymount University. His interests are in applied mathematics. Dr. Fitzpatrick received his Ph.D. and Sc. M. from Brown University in 1988 and 1986, respectively, and his M.P.S. and B.S. from Auburn University in 1983 and 1981, respectively.

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Robustness and Performance of Adaptive Suppression of Unknown Periodic Disturbances | IEEE Transactions on Automatic Control

2014-12-01

In recent years a class of adaptive schemes has been developed for suppressing periodic disturbance signals with unknown frequencies, phases, and amplitudes. The stability and robustness of these schemes with respect to inevitable unmodeled dynamics and noise disturbances in the absence of persistently exciting signals has not been established despite successful simulation results and implementations.

This paper investigates noise attenuation problems for systems with unmodelled dynamics and unknown noise characteristics. A unique methodology is introduced that employs signal estimation in one phase, followed by control design for noise rejection.

Forecasting the effect of the amethyst initiative on college drinking | Alcoholism Clinical and Experimental Research

2012-03-01

A number of college presidents have endorsed the Amethyst Initiative, a call to consider lowering the minimum legal drinking age (MLDA). Our objective is to forecast the effect of the Amethyst Initiative on college drinking.

Convergence and error bounds of adaptive filtering under model structure and regressor uncertainties | Journal of Control Theory and Applications

2012-01-01

Adaptive filtering algorithms are investigated when system models are subject to model structure errors and regressor signal perturbations. System models for practical applications are often approximations of high-order or nonlinear systems, introducing model structure uncertainties. Measurement and actuation errors cause signal perturbations, which in turn lead to uncertainties in regressors of adaptive filtering algorithms.

The present paper presents a preliminary approach to the modeling of dynamic properties of the spatial assortment of alcohol outlets using agent based techniques. Individual drinkers and business establishments are the core agent types. Drinkers assort themselves by frequenting establishments due to spatial and social (niche) motivations. We examine a number of questions concerning the feedback relationships between establishments targeting a particular niche clientele and the individuals seeking more desirable places to obtain alcohol.

In this paper, we examine three separate approaches to analyze the spatial dispersion of a subsurface contaminant. These methods are contrasted against traditional models to demonstrate their feasibility and usefulness. Lastly, numerical simulations illustrate the effectiveness of these approaches.